Systems and methods for analyzing colors from a social media platform

ABSTRACT

Systems and methods for color selection are provided and include a mobile device having a mobile application configured to access a social media platform, retrieve a plurality of images from the social media platform, determine a dominant color for each image of the plurality of images, determine a closest matching paint color for the dominant color for each image, and display at least one of a color name and a color code associated with the closest matching paint color for the dominant color for each image.

CROSS-REFERENCE TO RELATED APPLICATIONS

This application claims the benefit of U.S. Provisional Application No.62/519,657, filed on Jun. 14, 2017. The entire disclosure of the aboveapplication is incorporated herein by reference.

FIELD

The present disclosure relates to analyzing colors from a social mediaplatform and, more particularly, to color selection based on colorsretrieved from analyzed images on a social media platform.

BACKGROUND

This section provides background information related to the presentdisclosure, which is not necessarily prior art.

Consumers typically begin a new painting project because of a desire forchange. This typically stems from wanting a new look, wanting to changethe feeling of a room, being tired of the old look, boredom, seeing aninterior elsewhere, e.g., model home tour, friend's house, magazinephoto, etc.,

The home painting process typically starts with color selection, whichcan be an emotional part of the process. Many consumers are concernedwith making a mistake in the color selection process. Consequently, thecolor selection process can take several months to years to complete asthe user settles on a color.

Current systems for color selection allow a consumer to browse andselect particular colors electronically using, for example, a kiosk, awebsite, a web application, a mobile application, etc. For example, acolor selection and coordination system that allows a user to select astarting color and that provides coordinating colors for the startingcolor is described in U.S. Pat. No. 7,230,629, titled “Data-driven colorcoordinator,” which is incorporated herein by reference. For furtherexample, an automated method and apparatus for providing color selectioncapability is described in U.S. Pat. No. 9,530,163, titled “AutomatedColor Selection Method and Apparatus,” which is also incorporated hereinby reference.

SUMMARY

This section provides a general summary of the disclosure, and is not acomprehensive disclosure of its full scope or all of its features.

The present disclosure provides a system comprising a mobile devicehaving a mobile application configured to access a social mediaplatform, retrieve a plurality of images from the social media platform,determine a dominant color for each image of the plurality of images,determine a closest matching paint color for the dominant color for eachimage, and display at least one of a color name and a color codeassociated with the closest matching paint color for the dominant colorfor each image.

In some configurations, the mobile application is further configured todetermine and display a plurality of coordinating paint colors for theclosest matching paint color for the dominant color for each image.

In some configurations, the mobile application is further configured toenable a user to select a different color than the dominant color for animage of the plurality of images, to determine a closest matching colorfor the different color, and to display at least one of a color name anda color code associated with the closest matching color for thedifferent color.

In some configurations, the mobile application is further configured toupload an image that includes the closest matching paint color for thedominant color for each image to the social media platform.

In some configurations, the mobile application is further configured toreceive a selection of a particular image from the plurality of images,identify an object displayed in the particular image, and store theidentified object.

In another form, the present disclosure provides a method that includesretrieving, with a mobile device having a mobile application configuredto access a social media platform, a plurality of images from the socialmedia platform. The method also includes determining, with the mobiledevice, a dominant color for each image of the plurality of images. Themethod also includes determining, with the mobile device, a closestmatching paint color for the dominant color for each image. The methodalso includes displaying, with the mobile device, at least one of acolor name and a color code associated with the closest matching paintcolor for the dominant color for each image.

In some configurations, the method further comprises determining anddisplaying, with the mobile device, a plurality of coordinating paintcolors for the closest matching paint color for the dominant color foreach image.

In some configurations, the method also includes receiving, with themobile device, a selection from a user of different color than thedominant color for an image of the plurality of images. The method alsoincludes determining, with the mobile device, a closest matching colorfor the different color. The method also includes displaying, with themobile device, at least one of a color name and a color code associatedwith the closest matching color for the different color.

In some configurations, the method also includes uploading, with themobile device, an image that includes the closest matching paint colorfor the dominant color for each image to the social media platform.

In some configurations, the method also includes receiving, with themobile device, a selection of a particular image from the plurality ofimages, identifying an object displayed in the particular image, andstoring the identified object.

In another form, the present disclosure provides a non-transitorycomputer readable medium storing a mobile application for a mobiledevice. The mobile application includes computer executable instructionsto configure the mobile device to access a social media platform,retrieve a plurality of images from the social media platform, determinea dominant color for each image of the plurality of images, determine aclosest matching paint color for the dominant color for each image, anddisplay at least one of a color name and a color code associated withthe closest matching paint color for the dominant color for each image.

In some configurations, the mobile application further includes computerexecutable instructions to configure the mobile device to determine anddisplay a plurality of coordinating paint colors for the closestmatching paint color for the dominant color for each image.

In some configurations, the mobile application further includes computerexecutable instructions to configure the mobile device to enable a userto select a different color than the dominant color for an image of theplurality of images, to determine a closest matching color for thedifferent color, and to display at least one of a color name and a colorcode associated with the closest matching color for the different color.

In some configurations, the mobile application further includes computerexecutable instructions to configure the mobile device to upload animage that includes the closest matching paint color for the dominantcolor for each image to the social media platform.

In some configurations, the mobile application further includingcomputer executable instructions to configure the mobile device toreceive a selection of a particular image from the plurality of images,identify an object displayed in the particular image, and store theidentified object.

Further areas of applicability will become apparent from the descriptionprovided herein. The description and specific examples in this summaryare intended for purposes of illustration only and are not intended tolimit the scope of the present disclosure.

DRAWINGS

The drawings described herein are for illustrative purposes only ofselected embodiments and not all possible implementations, and are notintended to limit the scope of the present disclosure.

FIG. 1 is a block diagram of a system for analyzing colors from a socialmedia platform according to the present disclosure.

FIG. 2 is a block diagram of another system for analyzing colors from asocial media platform according to the present disclosure.

FIG. 3 is a screenshot of a system for analyzing colors from a socialmedia platform according to the present disclosure.

FIG. 4 is a screenshot of a system for analyzing colors from a socialmedia platform according to the present disclosure.

FIG. 5 is a screenshot of a system for analyzing colors from a socialmedia platform according to the present disclosure.

FIG. 6 is a screenshot of a system for analyzing colors from a socialmedia platform according to the present disclosure.

FIG. 7 is a screenshot of a system for analyzing colors from a socialmedia platform according to the present disclosure.

FIG. 8 is a screenshot of a system for analyzing colors from a socialmedia platform according to the present disclosure.

FIG. 9 is a screenshot of a system for analyzing colors from a socialmedia platform according to the present disclosure.

FIG. 10 is a screenshot of a system for analyzing colors from a socialmedia platform according to the present disclosure.

FIG. 11 is a screenshot of a system for analyzing colors from a socialmedia platform according to the present disclosure.

FIG. 12 is a flow chart for a method of analyzing colors from a socialmedia platform according to the present disclosure.

FIG. 13 is a block diagram of an image analysis system according to thepresent disclosure.

FIG. 14 is a diagram showing an analysis of pixels of an image by animage analysis system according to the present disclosure.

FIG. 15 is a flow chart for a method of analyzing images according tothe present disclosure.

Corresponding reference numerals indicate corresponding parts throughoutthe several views of the drawings.

DETAILED DESCRIPTION

Example embodiments will now be described more fully with reference tothe accompanying drawings.

The present disclosure includes systems and methods for analyzing colorsin images retrieved from a social media platform. For example, thesocial media platform may include a platform for uploading, saving,sorting, managing, and sharing images and/or collections of images. Forexample, a user may browse images uploaded by other users and may tag,bookmark, or save an image or collection of images that can then belater retrieved and viewed in the user's own area of the social mediaplatform. For example, the social media platform may be implementedthrough a mobile application, a website, and/or a web application. Forexample, the social media platform may be the PINTEREST® social mediaplatform by Pinterest, Inc., currently available at www.pinterest.comand through a mobile application. The systems and methods of the presentdisclosure can then analyze the images saved in the user's own area ofthe social media platform and present one or more dominant colors fromeach of the images. In particular, for each of the dominant colorsdetermined from each of the images, the systems and methods of thepresent disclosure can determine a closest matching paint colorassociated with each of the dominant colors and can present the userwith information, such as a paint color name and identification code,associated with each of the closest matching paint colors.

Once the paint colors are determined, the systems and methods of thepresent disclosure can provide coordinating colors or coordinating colorpalettes for each of the paint colors. The systems and methods of thepresent disclosure can be integrated with other color coordinationsystems and methods that allow the user to view the particular paintcolors in a simulated environment. For example, color coordinationsystems and methods that enable a user to view particular colors in asimulated environment are described in U.S. Pat. No. 7,230,629, titled“Data-driven color coordinator,” which is incorporated herein byreference. The systems and methods of the present disclosure can alsoenable a user to order samples of particular paint colors and saveinformation associated with the particular paint colors, such as colornames and identification codes, on a server for later retrieval by theuser.

Further, once particular paint colors, coordinating paint colors, and/orcoordinating paint color palettes are determined or selected, thesystems and methods of the present disclosure can generate an image ofthe particular paint colors, coordinating paint colors, and/orcoordinating paint color palettes that can be uploaded and saved intothe user's area of the social platform and shared with other users ofthe social media platform.

In this way, a user can browse images within the social media platformseeking inspiration for colors for a paint project. The user can theneasily translate dominant colors from particular images retrieved fromthe social media platform into paint colors and can view associatedcoordinating colors. As such, the systems and methods of the presentdisclosure can assist a user in quickly determining particular paintcolors for a paint project.

With reference to FIG. 1, a block diagram of a system 10 for analyzingcolors from a social media platform according to the present disclosureis shown. The system 10 includes a social media server 12 and a mobiledevice 14 in communication over a network 16. The social media server 12may be configured with one or more processors and with memory thatstores content, such as images. The network 16 may be a local areanetwork (LAN) or a wide area network (WAN), such as the internet. Thesocial media server 12 includes a network communication module tocommunicate with the mobile device 14 over the network 16.

The social media server 12 may host a social media platform foruploading, saving, sorting, managing, and sharing images and/orcollections of images. For example, the social media server 12 may hostthe PINTEREST® social media platform. In the example of the PINTEREST®social media platform, images are referred to as “pins.” The images orpins are then saved to the user's “pinboards” or “boards.” Users canbrowse each other's boards and save particular images to their ownboards. In this way, a user can save particular images or pins that areinteresting, inspirational, and/or that show particular colors ofinterest to the user's own board or area of the PINTEREST® social mediaplatform. As such, the user can build up a collection of images or pinsin the user's own board or area of the PINTEREST® social media platform.

The systems and methods of the present disclosure can be implementedthrough a mobile application. For example, the mobile device 14 can be asmartphone or a tablet device configured with a processor, a memory, andan input/output device, such as a touchscreen. The mobile device 14includes a network communication module to communicate with the socialmedia server 12 over the network 16. The systems and methods of thepresent disclosure can be implemented through a mobile applicationinstalled on the mobile device 14.

Additionally or alternatively, the systems and methods of the presentdisclosure can be implemented using webpages and/or web applications.For example, with reference to FIG. 2, a block diagram of another system11 for analyzing colors from a social media platform according to thepresent disclosure is shown. In FIG. 2, a user device 15 is incommunication with the social media server 12 and a web server 18. Theweb server 12 may be configured with one or more processors and withmemory that stores content, such as webpages in Hypertext MarkupLanguage (HTML), accessible to the user device 15 via a web browser thatnavigates to a website associated with the web server. For furtherexample, the color selection system 11 may be implemented within a webapplication, whereby the web server 18 provides code for the webapplication to the user device 15 and the web application runs in a webbrowser of the user device 15. Additionally or alternatively, the system11 according to the present disclosure may be implemented with astandalone application that runs on the user device 15 outside of abrowser while communicating with the web server 18 and the social mediaserver 12. The social media server 12 and the web server 18 each includea network communication module to communicate with the user device 15over the network 16.

The user device 15 is a computing device with input devices, such as akeyboard and a mouse, and a display device such as a display screen.Additionally or alternatively, the user device 14 may include a touchscreen device that both receives user input and displays output. Theuser device 15 includes one or more processors and memory. The memory ofthe user device 15 may store code for a web browser that accesses andretrieves content from websites, such as the website associated with theweb server 18. The memory of the user device 15 may also store code fora mobile application that provides the functionality of the colorselection systems and methods of the present disclosure. The user device15 may include a personal computer, a laptop, a tablet, and/or a mobiledevice, such as a smartphone, that utilizes a web browser. The userdevice 15 includes a network communication module to communicate withthe social media server 12 and the web server 18 over the network 16.

While examples of the systems and methods of the present disclosure arediscussed with reference to a mobile application for a mobile device 14,such as a smartphone or tablet device, as shown in FIG. 1, the systemsand methods of the present disclosure can be similarly implementedthrough a website or web application that runs in a web browser of auser device 15, as shown in FIG. 2.

With reference to FIG. 3, a screenshot of a first page 30 of a mobileapplication for implementing the system 10 according to the presentdisclosure is shown. The first page 30 includes a button 32 for logginginto the mobile application. The mobile application of the presentdisclosure can be integrated with a social media platform through anApplication Programming Interface, or API, made available for the socialmedia platform. For example, as discussed, the social media platform mayinclude the PINTEREST® social media platform and the mobile applicationof the present disclosure may integrate with the PINTEREST® social mediaplatform using the PINTEREST® API. For example, a user of the mobileapplication of the present disclosure may login in to the mobileapplication using the user's login and password for the social mediaplatform, such as the PINTEREST® social media platform. The mobileapplication may then user the API of the social media platform, such asthe PINTEREST® API, to access the user's saved content on the socialmedia platform. For example, in the example of the PINTEREST® socialmedia platform, the mobile application may use the PINTEREST® API toaccess and retrieve pins or images saved by the user on the user's thePINTEREST® board. Once the user clicks the login button 32, a secondpage 40 (shown in FIG. 4) is displayed on the display of the mobiledevice 14.

With reference to FIG. 4, the second page 40 includes multiple optionsto enable the user to login. For example, the user can login using alogin associated with the user's FACEBOOK® account. Additionally oralternatively, the user can login using a login associated with theuser's GOOGLE® account. Additionally or alternatively, the user canlogin with an email or phone number and a password. Once the user logsin, the mobile application can access and display content from theuser's area of the social media platform.

For example, as shown in FIG. 5, the mobile application can display athird page 50 that includes collections of images retrieved from theuser's area of the social media platform. For example, using thePINTEREST® social media platform example, the mobile application canretrieve boards, or collections of images, that have been saved by theuser or that are being followed by the user. In the example of the thirdpage 50 shown in FIG. 5, the user has selected two boards 52, 54. Thefirst board 52 is titled “Modern Architecture” and includes nine pins orimages. The second board 54 is titled “Mid-century Modern Furniture” andincludes 13 pins or images. Once the user has selected one or moreboards, the user press the “continue” button 56 and a fourth page 60(shown in FIG. 6) is displayed on the display of the mobile device 14.

With reference to FIG. 6, the fourth page 60 prompts the user to selectindividual images or pins from the boards selected in the previous step.For example, the third page 60 includes a board bar 62 that can beswiped left and/or right to view the various boards selected in theprevious step. In the example of FIG. 6, the Modern Architecture boardis selected and the individual pins or images saved within that boardare displayed below the board bar 62. The user can then selectindividual images or pins from each board. In the example of FIG. 6, theuser has selected a first image 64 and a second image 66 from the ModernArchitecture board. The user may select up to a predetermined number ofpins or images. For example, the mobile application may limit the userto selection of up to six pins or images. Once the user has selected thedesired pins or images, the user can press the “Create Palette” button68. Once the user presses the “Create Palette” button 68, a fifth page70 (shown in FIG. 7) is displayed on the display of the mobile device14.

With reference to FIG. 7, the fifth page 70 displays a color associatedwith each image or pin selected in the previous step. As discussed infurther detail below with respect to the image analysis tool, the mobileapplication can analyze the pixels in each image or pin and select adominant color associated with each image or pin. As shown in theexample of FIG. 7, a thumbnail bar 72 is shown across the top of thefifth page 70 displaying a thumbnail version of each image or pinselected in the previous step. In addition two rows 74, 76 are shownbeneath the thumbnail bar 72. The top row 74 displays three colorsassociated with the leftmost thumbnail images in the thumbnail bar 72.The bottom row 76 displays three colors associated with the rightmostthumbnail images in the thumbnail bar 72. The fifth page 70 alsoprovides the user with an option to click on a color to modify orexplore that color. The fifth page 70 also provides the user with anoption to click on “Paint Your Place” button 77 to enable the user toview one or more of the colors in a simulated environment. The fifthpage 70 also provides the user with an option to “Save to Pinterest”button, which saves the collection of colors in an image that is thensaved to the user's board or area of the social media platform, such asthe PINTEREST® social media platform. The fifth page 70 also providesthe user with an option to “Get Samples” button, which enables the userto order paint samples for one or more of the displayed colors in thefirst and second rows 74, 76. When the user clicks on a particularcolor, a sixth page 80 (shown in FIG. 8) is displayed on the display ofthe mobile device 14.

With reference to FIG. 8, the sixth page 80 displays a particular color81 selected from the individual colors presented in the previous step.In the example of FIG. 8, an enlarged square of the particular color 81is displayed in a central region of the sixth page 80, while a color bar82 shows all six individual colors from the previous step. Theparticular color selected is highlighted in the color bar 82 by beingsurrounded by a darker circle to indicate it is the currently selectedcolor. The name of the particular color 81 is displayed below theparticular color 81. In the case of FIG. 8, the name of the particularcolor 81 is “Underground Gardens” and the identification code associatedwith the color is N420-4. In addition, the sixth page 80 displayscoordinated palettes 85 for the particular color. For example, eachcolor coordinated palette of the coordinated palettes 85 shows theparticular color along with one or more coordinating colors for theparticular color. While four coordinated palettes 85 are shown in FIG.8, the user can retrieve additional coordinated palettes 85 by scrollingto the left or to the right using the arrow buttons. As further shown inFIG. 8, a delete button 84 is provided to allow the user to delete theparticular color from the group of colors shown in the color bar 82. Asfurther shown in FIG. 8, an edit button 83 is provided to enable theuser to choose a different color from the pin or image associated withthe particular color. When the user clicks on the edit button 83, aseventh page 90 (shown in FIG. 9) is displayed on the display of themobile device 14.

With reference to FIG. 9, the seventh page 90 displays the particularpin or image 92 associated with the particular color 81 from theprevious step. A smaller rectangle of the particular color 93 from theprevious step is shown below the particular pin or image 92. Inaddition, a color selection tool 94 appears in the particular pin orimage 92 at an initial location corresponding to one or more pixels thatcorrespond to the particular color. The user can then drag the colorselection tool 94 to other locations within the particular pin or image92 to view other colors within the pin or image 92. For example, oncethe color selection tool 94 is moved to another location within theparticular pin or image 92, the particular color 93 is updated toanother color that is the closest matching paint color to the color inthe particular pin or image 92 at the location indicated by the colorselection tool 94. For example, the mobile device 14 may have access toa paint color database and may search the paint color database to find aclosest matching paint color to the selected color in the particular pinor image 92 at the location indicated by the color selection tool 94 bycomparing color values, such as, for example, RBG (red, green, blue)color values, CMYK (cyan, magenta, yellow and key/black) color values,and/or CIE XYZ color values, of the selected color to color values ofindividual paint colors in the paint color database. Systems and methodsfor determining a closest matching paint color to a particular color aredescribed, for example, in commonly assigned U.S. Pat. No. 9,928,543,titled Data-Driven Color Coordinator, issued on Mar. 27, 2018, which isincorporated herein in its entirety. The paint color database may bestored on the mobile device 14 or may be stored remotely such that themobile device 14 can access the paint color database via communicationover the network 16. Once the user has selected a new color from theparticular pin or image 92, the user can then click the save button 95to save the new color to the group of selected colors from the previoussteps in place of the originally provided color. Alternatively, the usercan click the cancel button to cancel the current editing process. Inaddition, a thumbnail bar 97 is shown above the particular pin or image92. The user can click on a different pin or image from the thumbnailbar and similarly edit the color associated with that pin or image.

Returning to FIG. 7, once the user is satisfied with the group ofcolors, the user can select the “Save to Pinterest” button to save animage of the group of colors to the user's area of the social mediaplatform. For example, the user can save an image of the group of colorsto a particular board within the PINTEREST® social media platform. Oncethe user clicks the “Save to Pinterest” button 78, an eighth page 100(shown in FIG. 10) is displayed on the display of the mobile device 14.

With reference to FIG. 10, the eighth page 100 displays an image 102 ofthe group of colors from the previous steps. The eighth page alsoprompts the user to select a particular board or group of images fromthe social media platform. For example, the user can select the ModernArchitecture board 103, shown in FIG. 10. Once the user selects aparticular board, a ninth page 110 (shown in FIG. 11) is displayed onthe display of the mobile device 14.

With reference to FIG. 11, the ninth page 110 shows the image 102 of thegroup of colors displayed on the board selected in the previous step,e.g., the Modern Architecture board. At this point, the mobileapplication returns to the fourth page 60 shown in FIG. 6 and promptsthe user to select individual images to create a palette.

With reference to FIG. 12, a flow chart for a method 1200 according tothe present disclosure is illustrated. The method 1200 can be executedby the mobile device or tablet 14 and starts at 1202. At 1204, aparticular board or group of images is received from the social mediaplatform, as described in detail above with reference to FIG. 5. At1206, particular images or pins are selected from the selected boards,as discussed in detail above with reference to FIG. 6.

At 1208, dominant colors for each of the images/pins selected in theprevious step are determined and displayed, as described in detail abovewith reference to FIG. 7 and below with reference to FIGS. 13 to 15.

At 1210, a selection for a particular color from the group of displayedcolors is received, as discussed in detail above with reference to FIGS.7 and 8. At 1212, coordinating color palettes are displayed for theparticular color selected, as discussed in detail above with referenceto FIG. 8.

At 1212, options are displayed for: (1) editing a particular color, asdiscussed in detail above with reference to FIG. 8; (2) generating asimulated environment with the colors or color palettes, as discussed indetail above with reference to FIG. 7; (3) saving an image of the colorsto the social media platform, as discussed in detail above withreference to FIGS. 7, 10, and 11; and (4) ordering samples of thecolors, as discussed in detail above with reference to FIG. 7. At 1216,the selected option is carried out, as discussed in detail above withreference to the noted Figures. At 1218, the method 1200 ends.

In this way, the systems and methods of the present disclosure enable auser to quickly and efficiently retrieve and view colors from imagessaved and shared on a social media platform and, in particular,corresponding paint colors associated with the colors from the socialmedia platform.

The systems and methods for analyzing colors in images retrieved fromthe social media platform may additionally track the particular imagesthat are selected by individual users to analyze the types of imagesthat users find helpful or inspirational in selecting paint colors,which may be helpful for determining the types of images to be used formarketing to the users. For example, once a particular image is selectedby a user, the mobile device 14, or an additional server incommunication with the mobile device 14, can utilize an image analysistool to determine the content of the image and identify individualobjects within the particular image. For example, the mobile device 14,or an additional server in communication with the mobile device 14, canutilize the CLOUD VISION API tool available through GOOGLE, whichclassifies images into categories, detects individual objects within theimages (e.g., “sailboat,” “lion,” “Eiffel Tower,” “living room,” “tree,”“beach,” “sunset,” etc.). For example, a particular image selected fromthe social media platform may have a particular Uniform Resource Locator(URL) associated with it. The system can retrieve the particular URL forthe image and submit it to the image analysis tool, such as the CLOUDVISION API tool available through GOOGLE, which will analyze the imageand output a listing of the individual objects detected in the image.The systems and methods of the present disclosure can then track andstore the content present within the individual images selected by usersand track any trends with respect to whether certain types of contentwith the image is selected more often than other types of content.

In this way, the systems and methods of the present disclosure can trackwhether particular objects in an image are more popular than other or,for example, more popular with certain types of users or users in aparticular demographic. For example, the systems and methods of thepresent disclosure can analyze rankings for individual objects anddetermine trends for selections made by users within a certaindemographic. For example, the systems and methods of the presentdisclosure may determine that images of tea kettles are popular withusers in the northeast area of the United States. That information couldthen be used, for example, to create marketing materials showing imagesof tea kettles directed to users in the northeast area of the UnitedStates.

In addition, the systems and methods of the present disclosure canidentify trends with respect to particular objects in an image selectedby a particular user. For example, if a particular user most oftenselects images with objects such as trees, lakes, and beaches, thesystems and methods of the present disclosure may determine that theparticular user selects images with nature scenes more frequently thanother scenes. In this way, the systems and methods of the presentdisclosure can identify the types of images that are popular for aparticular user and/or can classify individual users based on theirimage selections. For example, the systems and methods of the presentdisclosure could classify a particular user in an “outdoor” group ofusers and then present targeting marketing to the particular user basedon the classification. For example, users in the “outdoor” group ofusers may be presented with marketing that utilizes outdoor scenes,based on the identified classification.

With reference to FIGS. 13 to 15, systems and methods for determiningdominant colors in an image are shown. With reference to FIG. 13, asystem 1300 for determining dominant colors in an image is shown. Thesystem 1300 can include a computing device 1302. The computing devicecan be a personal computer, a laptop, a mobile device, a table, oranother suitable computing device with a processor and memory forcarrying out the functionality described herein. The computing deviceincludes an image analysis module 1304. The image analysis module 1304,for example, can be implemented as part of the mobile application forthe mobile device 14 described in detail above.

The image analysis module 1304 receives an image 1306 as input. Theimage analysis module 1304 analyzes the received image and generatesoutput 1308 including one or more dominant colors from the image 1306.

In particular, the image analysis module 1304 analyzes individual pixelswithin an image file, starting at the center of the image and workingoutward from the center in a spiral fashion. As the image analysismodule 1304 gets further from the center of the image, the sampling rateis decreased such that pixels towards the center of the image aresampled at a higher rate than pixels towards the edge of the image. Inthis way, the pixels near the center are weighted more heavily thanpixels away from the center and towards the edge of the image. Inaddition, low level chroma colors, such as pixels with colors that arebelow a predetermined chroma value threshold, i.e., very dull or mutedcolors, are excluded. In addition, low lightness colors, such as pixelswith a lightness level below a brightness threshold, i.e., very darkcolors, are also excluded. Further, high lightness colors, such aspixels with a lightness level above a brightness threshold, i.e., verybright colors, are also excluded. All remaining sampled colors arecounted, with similar colors being grouped together. The image analysismodule 1304 then determines the color, or group of similar colors, withthe highest count and returns that color, or a representative of thegroup of similar colors, as the dominant color for the image.

With reference to FIG. 14, an example image 1400 is shown broken up intoindividual pixel squares, labelled by column and row, in the format of:row, column. For example, the upper left pixel is labelled as row,column: 1,1. The upper right pixel is labeled as row, column: 1,5. Thelower left pixel is labelled as row, column: 7,1. The lower right pixelis labelled as row, column 7,5.

In this example, the sequence of analysis is indicated by the arrows andstarts in the center of the image at pixel 4,3. Pixels that are includedin the analysis of the image are shown with a white square. Pixels thatare skipped or excluded from the analysis are shown grayed out.

Starting from the center of the image 1400, the image analysis module1304 includes the first four pixels (i.e., 4,3; 4,4; 5,4; and 5,3) inthe analysis. Then, starting at pixel 5,2, the image analysis module1304 begins to analyze every other pixel. In other words, after pixel5,3, the next four pixels analyzed are pixels: 4,2; 3,3; 3,5; and 5,5.Then, starting at pixel 6,5, the image analysis module 1304 begins toskip two pixels for every one pixel included in the analysis. Forexample, after pixel 5,5, the next five pixels analyzed are pixels: 6,3;5,1; 2,1; 2,4; and 7,4. Then, starting at pixel 7,4, the image analysismodule 1304 begins to skip three pixels for every one pixel analyzed. Assuch, after 7,4, the next three pixels analyzed are pixels: 1,1 and 1,5.

In this way, the image analysis module 1304 decreases the pixel samplerate by skipping more and more pixels as it moves away from the centerof the image. With respect to the remaining non-skipped pixels, theimage analysis module 1304 applies the above described filters for lowchroma values, low lightness values, and high lightness values. Theremaining pixels are then analyzed with similar pixel colors beinggrouped together. Based on the number of colors or similar pixel colorgroups, the image analysis module then determines one or more dominantcolors for the image 1400.

With reference to FIG. 15, a method 1500 for analyzing images accordingto the present disclosure is shown. The method 1500 can be executed bythe image analysis module 1304 of the computing device 1302 and startsat 1502. At 1504, the image analysis module receives the image. At 1506,the image analysis module 1304 divides the pixels of the image intosubgroups, with each of the subgroups being analyzed with a differentsampling rate. Using the example image of FIG. 14, the first subgroupwould include pixels: 4,3; 4,4; 5,4; and 5,3. The second subgroup wouldinclude pixels: 5,2; 4,2; 3,2; 3,3; 3,4; 3,5; 4,5; and 5,5. The thirdsubgroup would include pixels: 6,5; 6,4; 6,3; 6,2; 6,1; 5,1; 4,1; 3,1;2,1; 2,2; 2,3; 2,4; 2,5; 7,5, and 7,4. The fourth subgroup would includepixels: 7,3; 7,2; 7,1; 1,1; 1,2; 1,3; 1,4; and 1,5.

At 1508, the image analysis module analyzes the different subgroupsusing different sample rates. For example, every pixel of the firstsubgroup is analyzed. Every other pixel of the second subgroup isanalyzed. Every third pixel of the third subgroup is analyzed. Everyfourth pixel of the fourth subgroup is analyzed. While four differentsampling rates for four different subgroups are described with referenceto FIGS. 14 and 15, any number of subgroups of pixels and any number ofsampling rates can be used. Further, the image analysis module 1304 canuse different processing threads to perform the analysis of the varioussubgroups concurrently.

Also at 1508, the individual pixels are analyzed based on theexclusionary rules discussed above. For example, any pixels with colorshaving a chroma value that is below a chroma threshold and are too dullor muted are excluded. Any pixels with colors having a lightness valuethat is below a lightness threshold and are too dark are excluded. Anypixels with colors having a lightness value that is above a lightnessthreshold and are too bright are excluded. In addition, similar colors,i.e., colors that have hue, chroma, and lightness/darkness values thatare within a predetermined threshold of each other, are groupedtogether. For each subgroup, the totals for the different colors orgroups of similar colors are tallied by the image analysis module 1304.

At 1510, the totals from the individual subgroups are combined such thatthe same colors or similar color groups are added together.

At 1512, the image analysis module then determines the dominant color orcolors based on the totals. In other words, the color or color groupwith the highest total is deemed the dominant color for the image.

The method ends at 1514.

The foregoing description of the embodiments has been provided forpurposes of illustration and description. It is not intended to beexhaustive or to limit the disclosure. Individual elements or featuresof a particular embodiment are generally not limited to that particularembodiment, but, where applicable, are interchangeable and can be usedin a selected embodiment, even if not specifically shown or described.The same may also be varied in many ways. Such variations are not to beregarded as a departure from the disclosure, and all such modificationsare intended to be included within the scope of the disclosure.

The terms server, user device, computing device, and module may referto, be part of, or include an Application Specific Integrated Circuit(ASIC); a digital, analog, or mixed analog/digital discrete circuit; adigital, analog, or mixed analog/digital integrated circuit; acombinational logic circuit; a field programmable gate array (FPGA); aprocessor (shared, dedicated, or group) that executes code; memory(shared, dedicated, or group) that stores code executed by a processor;other suitable hardware components that provide the describedfunctionality; or a combination of some or all of the above, such as ina system-on-chip.

The term code, as used above, may include software, firmware, and/ormicrocode, and may refer to programs, routines, functions, classes,and/or objects. The term shared processor encompasses a single processorthat executes some or all code from multiple modules. The term groupprocessor encompasses a processor that, in combination with additionalprocessors, executes some or all code from one or more modules. The termshared memory encompasses a single memory that stores some or all codefrom multiple modules. The term group memory encompasses a memory that,in combination with additional memories, stores some or all code fromone or more modules. The term memory may be a subset of the termcomputer-readable medium. The term computer-readable medium does notencompass transitory electrical and electromagnetic signals propagatingthrough a medium, and may therefore be considered tangible andnon-transitory. Non-limiting examples of a non-transitory tangiblecomputer readable medium include nonvolatile memory, volatile memory,magnetic storage, and optical storage.

The servers, user devices, apparatuses, and methods described in thisapplication may be partially or fully implemented with or by one or morecomputer programs executed by one or more processors. The computerprograms include processor-executable instructions that are stored on atleast one non-transitory tangible computer readable medium. The computerprograms may also include and/or rely on stored data.

Example embodiments are provided so that this disclosure will bethorough and will fully convey the scope to those who are skilled in theart. Numerous specific details are set forth such as examples ofspecific components, devices, and methods, to provide a thoroughunderstanding of embodiments of the present disclosure. It will beapparent to those skilled in the art that specific details need not beemployed, that example embodiments may be embodied in many differentforms and that neither should be construed to limit the scope of thedisclosure. In some example embodiments, well-known processes,well-known device structures, and well-known technologies are notdescribed in detail.

The terminology used herein is for the purpose of describing particularexample embodiments only and is not intended to be limiting. As usedherein, the singular forms “a,” “an,” and “the” may be intended toinclude the plural forms as well, unless the context clearly indicatesotherwise. The terms “comprises,” “comprising,” “including,” and“having,” are inclusive and therefore specify the presence of statedfeatures, integers, steps, operations, elements, and/or components, butdo not preclude the presence or addition of one or more other features,integers, steps, operations, elements, components, and/or groupsthereof. The method steps, processes, and operations described hereinare not to be construed as necessarily requiring their performance inthe particular order discussed or illustrated, unless specificallyidentified as an order of performance. It is also to be understood thatadditional or alternative steps may be employed.

Spatially relative terms, such as “inner,” “outer,” “beneath,” “below,”“lower,” “above,” “upper,” and the like, may be used herein for ease ofdescription to describe one element or feature's relationship to anotherelement(s) or feature(s) as illustrated in the figures. Spatiallyrelative terms may be intended to encompass different orientations ofthe device in use or operation in addition to the orientation depictedin the figures. For example, if the device in the figures is turnedover, elements described as “below” or “beneath” other elements orfeatures would then be oriented “above” the other elements or features.Thus, the example term “below” can encompass both an orientation ofabove and below. The device may be otherwise oriented (rotated 90degrees or at other orientations) and the spatially relative descriptorsused herein interpreted accordingly.

What is claimed is:
 1. A system comprising: a mobile device having amobile application configured to access a social media platform,retrieve a plurality of images from the social media platform, determinea dominant color for each image of the plurality of images, determine aclosest matching paint color for the dominant color for each image, anddisplay at least one of a color name and a color code associated withthe closest matching paint color for the dominant color for each image;wherein the mobile application is further configured to determine thedominant color for each image of the plurality of images by dividing theimage into a plurality of pixel groups, analyzing pixels in each of thepixel groups at different sample rates based on how close the pixelgroup is to the center of the image with pixel groups closer to thecenter of the image having a higher sample rate, and determining thedominant color for the image based on the analyzed pixels in each of thepixel groups.
 2. The system recited by claim 1, the mobile applicationbeing further configured to determine and display a plurality ofcoordinating paint colors for the closest matching paint color for thedominant color for each image.
 3. The system recited by claim 1, themobile application being further configured to enable a user to select adifferent color than the dominant color for an image of the plurality ofimages, to determine a closest matching color for the different color,and to display at least one of a color name and a color code associatedwith the closest matching color for the different color.
 4. The systemrecited by claim 1, the mobile application being further configured toupload an image that includes the closest matching paint color for thedominant color for each image to the social media platform.
 5. Thesystem recited by claim 1, the mobile application being furtherconfigured to receive a selection of a particular image from theplurality of images, identify an object displayed in the particularimage, and store the identified object.
 6. A method comprising:retrieving, with a mobile device having a mobile application configuredto access a social media platform, a plurality of images from the socialmedia platform; determining, with the mobile device, a dominant colorfor each image of the plurality of images by dividing the image into aplurality of pixel groups, analyzing pixels in each of the pixel groupsat different sample rates based on how close the pixel group is to thecenter of the image with pixel groups closer to the center of the imagehaving a higher sample rate, and determining the dominant color for theimage based on the analyzed pixels in each of the pixel groups;determining, with the mobile device, a closest matching paint color forthe dominant color for each image; and displaying, with the mobiledevice, at least one of a color name and a color code associated withthe closest matching paint color for the dominant color for each image.7. The method recited by claim 6, further comprising determining anddisplaying, with the mobile device, a plurality of coordinating paintcolors for the closest matching paint color for the dominant color foreach image.
 8. The method recited by claim 6, further comprising:receiving, with the mobile device, a selection from a user of differentcolor than the dominant color for an image of the plurality of images;determining, with the mobile device, a closest matching color for thedifferent color; and displaying, with the mobile device, at least one ofa color name and a color code associated with the closest matching colorfor the different color.
 9. The method recited by claim 6, furthercomprising uploading, with the mobile device, an image that includes theclosest matching paint color for the dominant color for each image tothe social media platform.
 10. The method recited by claim 6, furthercomprising receiving, with the mobile device, a selection of aparticular image from the plurality of images, identifying an objectdisplayed in the particular image, and storing the identified object.11. A non-transitory computer readable medium storing a mobileapplication for a mobile device, the mobile application includingcomputer executable instructions to configure the mobile device toaccess a social media platform, retrieve a plurality of images from thesocial media platform, determine a dominant color for each image of theplurality of images, determine a closest matching paint color for thedominant color for each image, and display at least one of a color nameand a color code associated with the closest matching paint color forthe dominant color for each image; wherein the mobile applicationfurther includes computer executable instructions to determine thedominant color for each image of the plurality of images by dividing theimage into a plurality of pixel groups, analyzing pixels in each of thepixel groups at different sample rates based on how close the pixelgroup is to the center of the image with pixel groups closer to thecenter of the image having a higher sample rate, and determining thedominant color for the image based on the analyzed pixels in each of thepixel groups.
 12. The non-transitory computer readable medium recited byclaim 11, the mobile application further including computer executableinstructions to configure the mobile device to determine and display aplurality of coordinating paint colors for the closest matching paintcolor for the dominant color for each image.
 13. The non-transitorycomputer readable medium recited by claim 11, the mobile applicationfurther including computer executable instructions to configure themobile device to enable a user to select a different color than thedominant color for an image of the plurality of images, to determine aclosest matching color for the different color, and to display at leastone of a color name and a color code associated with the closestmatching color for the different color.
 14. The non-transitory computerreadable medium recited by claim 11, the mobile application furtherincluding computer executable instructions to configure the mobiledevice to upload an image that includes the closest matching paint colorfor the dominant color for each image to the social media platform. 15.The non-transitory computer readable medium recited by claim 11, themobile application further including computer executable instructions toconfigure the mobile device to receive a selection of a particular imagefrom the plurality of images, identify an object displayed in theparticular image, and store the identified object.